The Utility of Higher-Order Statistics in Gaussian Noise Suppression

Abstract

The properties of higher-order statistics are becoming more and more thoroughly studied in the field of signal processing. One property of great interest is the fact that the cumulants of Gaussian signals disappear entirely at higher orders. Because many noise and interference signals have Gaussian distributions, this property offers the possibility that higher-order statistics may be useful in signal recovery or interference mitigation, which would be of great advantage in military communications, intelligence, or surveillance systems. This thesis examines some of the theory behind higher-order statistics, and discusses the estimation of third-order cumulant values for several random variable distributions. After a minimum sample size has been determined, the study progresses to the frequency domain for an examination of the bispectra of the distributions. The thesis then explores the bispectra of non-Gaussian signals in the presence of Gaussian noise, and concludes with recommendations for implementing signal processing systems which utilize higher-order statistics.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2003
Accession Number
ADA414802

Entities

People

  • Donald R. Green

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Computer Programs
  • Data Science
  • Data Sets
  • Department Of Defense
  • Distribution Functions
  • Electrical Engineering
  • Engineering
  • Estimators
  • Gaussian Distributions
  • Gaussian Noise
  • Image Processing
  • Noise
  • Normal Distribution
  • Order Statistics
  • Probability Density Functions
  • Random Variables
  • Signal Processing

Fields of Study

  • Engineering

Readers

  • Economics
  • Radar Systems Engineering.
  • Statistical inference.

Technology Areas

  • Fully Networked C3
  • Fully Networked C3 - Command and Control